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+---
+Title: '.mul()'
+Description: 'Performs element-wise multiplication of two tensors or multiplies a tensor by a scalar.'
+Subjects:
+  - 'Computer Science'
+  - 'Machine Learning'
+Tags:
+  - 'Deep Learning'
+  - 'PyTorch'
+  - 'Tensors'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/machine-learning'
+---
+
+The **`.mul()`** function multiplies each element in the input [tensor](https://www.codecademy.com/resources/docs/pytorch/tensors) with another tensor or a scalar and returns a tensor of the same shape as the input (or broadcasted shape when inputs have different shapes).
+
+## Syntax
+
+```pseudo
+torch.mul(input, other, *, out=None) → Tensor
+```
+
+**Parameters:**
+
+- `input` (Tensor): Input tensor.
+- `other` (Tensor or Integer): The second input can be another tensor or a scalar value.
+- `out` (Tensor, optional): Optional tensor to store the output.
+
+**Return value:**
+
+Returns a new tensor containing the result of the operation, or modifies the `out` tensor if provided.
+
+## Example 1: Applying `.mul()` with a 1D tensor and a scalar
+
+In this example, `.mul()` multiplies a 1D tensor and a scalar:
+
+```py
+import torch
+
+# Create a tensor
+x = torch.tensor([1, 2, 3])
+
+# Multiply by scalar
+result = torch.mul(x, 2)
+
+print(result)
+```
+
+The output of this code is:
+
+```shell
+tensor([2, 4, 6])
+```
+
+## Example 2: Using `.mul()` with two 1D tensors
+
+In this example, `.mul()` multiplies each element in a 1D tensor with another 1D tensor:
+
+```py
+import torch
+
+# Create a tensor
+x = torch.tensor([1.0, 2.0, 3.0])
+# Create a second tensor
+y = torch.tensor([4.0, 5.0, 6.0])
+
+# Multiply by tensor
+result = torch.mul(x, y)
+
+print(result)
+```
+
+The output of this code is:
+
+```shell
+tensor([ 4., 10., 18.])
+```
+
+## Example 3: Using `.mul()` with a 2D tensor and a 1D tensor
+
+In this example, `.mul()` multiplies a 2D tensor with a 1D tensor using broadcasting:
+
+```py
+import torch
+
+# Create a 2x3 tensor
+x = torch.tensor([[1.0, 2.5, 3.0],[4.0, 5.0, 6.5]])
+# Create a second tensor
+y = torch.tensor([7.0, 8.0, 9.1])
+
+# Multiply by tensor
+result = torch.mul(x, y)
+
+print(result)
+```
+
+The output of this code is:
+
+```shell
+tensor([[ 7.0000, 20.0000, 27.3000],
+        [28.0000, 40.0000, 59.1500]])
+```